Journal
JOURNAL OF NEURAL TRANSMISSION
Volume 130, Issue 7, Pages 937-947Publisher
SPRINGER WIEN
DOI: 10.1007/s00702-023-02659-w
Keywords
Dopaminergic medication; Parkinson's disease; Smartphone; Finger tapping; Fluctuation; Feasibility; Repeatability
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This study aims to assess the feasibility and accuracy of a smartphone-based tapping task to distinguish medication status in Parkinson's disease patients. The study found that the task compliance was good and it can effectively discriminate between ON-OFF states. However, replication of these results in a wider sample is needed to confirm the reliability of the findings.
Tapping tasks have the potential to distinguish between ON-OFF fluctuations in Parkinson's disease (PD) possibly aiding assessment of medication status in e-diaries and research. This proof of concept study aims to assess the feasibility and accuracy of a smartphone-based tapping task (developed as part of the cloudUPDRS-project) to discriminate between ON-OFF used in the home setting without supervision. 32 PD patients performed the task before their first medication intake, followed by two test sessions after 1 and 3 h. Testing was repeated for 7 days. Index finger tapping between two targets was performed as fast as possible with each hand. Self-reported ON-OFF status was also indicated. Reminders were sent for testing and medication intake. We studied task compliance, objective performance (frequency and inter-tap distance), classification accuracy and repeatability of tapping. Average compliance was 97.0% (+/- 3.3%), but 16 patients (50%) needed remote assistance. Self-reported ON-OFF scores and objective tapping were worse pre versus post medication intake (p < 0.0005). Repeated tests showed good to excellent test-retest reliability in ON (0.707 <= ICC <= 0.975). Although 7 days learning effects were apparent, ON-OFF differences remained. Discriminative accuracy for ON-OFF was particularly good for right-hand tapping (0.72 <= AUC <= 0.80). Medication dose was associated with ON-OFF tapping changes. Unsupervised tapping tests performed on a smartphone have the potential to classify ON-OFF fluctuations in the home setting, despite some learning and time effects. Replication of these results are needed in a wider sample of patients.
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